MUMM
Validation SIMEC adjacency correction for
Coastal and Inland Waters
Sindy Sterckx1, Els Knaeps1, Susanne Kratzer2,4, Kevin Ruddick3, Ana Ruescas4
1
Flemish Institute for Technological Research (VITO) , Belgium
2 Department of Systems Ecology, Stockholm University, Sweden
3 Royal Belgian Institute for Natural Sciences (RBINS), Dept VI Management of the North Sea Mathematical Models (MUMM) , Belgium
4 Brockmann Consult, Germany
Introduction
Several new satellites such as Sentinel-2, Sentinel-3 and the hyperspectral satellites EnMAP and PRISMA will be launched in the near future. These EO sensors will provide
a wealth of new data at increased spatial, spectral and temporal resolutions. Although not all conceived as being ocean colour missions, the inland and coastal water
community could benefit considerably from these new data sources. A higher spatial resolution extends the existing monitoring efforts to cover even the first nautical mile
from coast where the Water Framework Directive (WFD) is still in force or to lakes which are small and have irregular shapes and can not be monitored with the existing
missions. However for these nearshore coastal and inland waters adjacency effects complicate the atmospheric correction process. Light reflected from the nearby land can
be forward scattered by the atmosphere into the sensor’s field of view. This causes a “blurring” of the signal and the effect, generally known as adjacency, background or
environment effect, modifies the spectral signature of the observed pixel. Here we present SIMEC (SIMilarity Environment Correction), a new approach for the correction of
adjacency effects.
SIMEC
The SIMEC correction method was first proposed by Sterckx et al. (2010) for the correction of airborne
hyperspectral imagery. The correction algorithm estimates the contribution of the background radiance based on
the correspondence with the NIR similarity spectrum (Ruddick et al., 2006). A key aspect of the method is that no
assumptions have to be made on the NIR albedo.
Validation approach
SIMEC is applied to correct the TOA radiance signal for adjacency effects for a
series of MERIS FR data covering the Belgian North Sea coastal waters, the
turbid Scheldt estuary and lake Vänern in Sweden, the third largest lake in
Europe. Next, the standard MERIS processor (MEGS) is applied using the
ODESA (Optical Data processor of ESA) software, in order to retrieve the water
reflectance and to compare with in-situ measured water reflectance.
Results and discussion
The normalized water reflectance retrieved from ODESA-MEGS processing on MERIS FR images with and without
first applying SIMEC are compared to the in-situ measured normalized water reflectance. For several sampling
stations the MERIS retrieved normalized water reflectance is strongly underestimated without SIMEC preprocessing with often negative water reflectance values for the first two MERIS bands. The correspondence
between MERIS retrieved normalized water reflectance and in-situ measured normalized water are quantified on
the basis of the Root Mean Square Error (RMSE) and the correlation coefficient (R²). A significant decrease in
RMSE and increase in R² is observed for several stations after SIMEC pre-processing.
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Quality indicators for spectral correspondence between in-situ normalized water reflectance and
MERIS MEGS retrieved normalized water reflectance with and without SIMEC pre-processing.
Conclusions
A new approach for the correction of adjacency effects which was originally developed for high resolution hyperspectral airborne data was presented in this poster. SIMEC
is a sensor-generic approach and can therefore be applied to future sensors such as Sentinel-2 MSI, Sentinel-3 OLCI and EnMAP/PRISMA data. The performance of
SIMEC was tested on MERIS FR images acquired over coastal areas, estuaries and lakes. SIMEC had a positive or neutral effect on the retrieved water reflectance
calculated with the MERIS MEGS processor. A decrease in the RMSE up to 400 % was observed after SIMEC pre-processing.
Acknowledgement :
This work was funded in the framework of the INTERREG 2Seas ISECA project